Simulation Study of Collaborative Inventory Management for Seasonal Products by Incorporating Newsvendor and Buyback Contract

Abstract

As supply chains become leaner, supply chain (SC) managers are often subjected to decrease inventory. Determining the appropriate inventory level for seasonal products without compromising the level of service provided to customers is crucial. This poses a challenge for supply chain managers to find the best trade-off between having excess or less inventory. A well-known model to determine such trade-offs is the newsvendor model. This model is focused on a decentralized business strategy. This research seeks to evaluate the contributions of collaborative inventory management for seasonal products with demand uncertainties having a single order in a cycle through newsvendor and buyback contract for a two-tier SC for both decentralized and centralized business strategies. To explore the effects of these uncertainties on seasonal products such as newspaper, apparels, perishable foods and major holiday products, a Monte Carlo simulation model was used to optimize the decision variable (the maximum order quantity, Q*) to improve the financial performance of the SC. The results indicate that wholesale price discount and buyback contract are efficient in collaborative inventory management. Buyback contract is less attractive when costs associated with returns are high. High return costs reduce the profitability of the SC significantly.